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Certified Advanced AI Engineer

Advanced AI Engineering

Track Goal

Equip experienced developers and engineers to design, train, and deploy production-grade, scalable AI systems.

Ideal For

Software Developers, Data Engineers, and IT Professionals seeking to specialize in AI.

6–7 months
Duration
7
Classes
Certificate
Upon Completion
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Class Curriculum

1

Advanced Python for AI Engineering

4 topics🎯 Project-Based

What you'll learn:

Advanced OOP for building scalable ML systems
Mastery of NumPy, Pandas, and Scikit-learn
Performance optimization and working with large datasets
API development principles with FastAPI/Flask
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Project:

Build a high-performance data processing pipeline or a custom ML model library.

2

Advanced Machine Learning

3 topics🎯 Project-Based

What you'll learn:

Advanced feature engineering and selection
Ensemble models (Random Forests, XGBoost, LightGBM)
Model explainability (SHAP, LIME) and bias mitigation
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Project:

Compete in a Kaggle-level modeling challenge using advanced ensemble techniques.

3

Deep Learning Masterclass

3 topics🎯 Project-Based

What you'll learn:

In-depth CNNs, LSTMs, GRUs, and Attention models
Transfer learning, dropout, and advanced optimization techniques
Modern architectures (e.g., Transformers)
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Project:

Build a complex image classifier or a text generation model.

4

Generative AI & LLMs

4 topics🎯 Project-Based

What you'll learn:

Transformer architecture deep-dive
Fine-tuning models (GPT, LLaMA, Gemini)
Retrieval-Augmented Generation (RAG) pipelines
LangChain & vector databases (Chroma, Pinecone)
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Project:

Build a domain-specific Q&A chatbot using RAG and a vector database.

5

MLOps and AI Deployment

4 topics🎯 Project-Based

What you'll learn:

Building APIs for models (FastAPI, Flask)
Containerization with Docker & Kubernetes
CI/CD pipelines for ML systems (GitHub Actions, Jenkins)
Cloud deployment (AWS SageMaker, GCP Vertex AI)
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Project:

Deploy an end-to-end ML model as a scalable API on a cloud platform.

6

Specialization Elective

2 topics🎯 Project-Based

What you'll learn:

Topics: Healthcare AI, Finance AI, Retail AI, or Supply Chain AI
Study domain-specific models, data, and regulations
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Project:

Develop and (sim)deploy an AI solution for your chosen domain.

7

Capstone: End-to-End AI Product

2 topics📋 Outcome-Based

What you'll learn:

Ideate and build a full-stack AI system: data pipeline → model → API → simple frontend
Write documentation, tests, and present your final product
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Outcome:

A fully deployed, end-to-end AI product to showcase to employers.

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Join this track and earn your Certified Advanced AI Engineer certification

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